By Wei Lee Woon, Zeyar Aung, Stuart Madnick
This ebook constitutes revised chosen papers from the second one ECML PKDD Workshop on info Analytics for Renewable power Integration, DARE 2014, held in Nancy, France, in September 2014. The eleven papers provided during this quantity have been conscientiously reviewed and chosen for inclusion during this book.
Read Online or Download Data Analytics for Renewable Energy Integration: Second ECML PKDD Workshop, DARE 2014, Nancy, France, September 19, 2014, Revised Selected Papers PDF
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Extra info for Data Analytics for Renewable Energy Integration: Second ECML PKDD Workshop, DARE 2014, Nancy, France, September 19, 2014, Revised Selected Papers
To solve (1), it is rewritten as a constrained minimization problem: min W,b,ξ 1 W 2 2 (ξt + ξt∗ ), +C (2) t subject to the restrictions W · Xt + b − yt ≥ −ξt − , W · Xt + b − yt ≤ ξt∗ + and ξt , ξt∗ ≥ 0. Its dual problem is then obtained by Lagrangian theory, that yields min Θ(α, β) = 1 2 (αt − βt )(αs − βs )Xt · Xs + t,s (αt + βt ) − t yt (αt − βt ) (3) t which has much simpler box constraints 0 ≤ αt , βt ≤ C. The Karush–Kuhn– Tucker (KKT) conditions for problems (2) and (3) can be applied to compute the optimal W ∗ , b∗ of the primal problem from the optimal dual solutions αt∗ , βt∗ , yielding a ﬁnal model f (X) = f (X, W ∗ , b∗ ) = W ∗ · X + b∗ = (αt∗ − βt∗ )Xt · X + b∗ .
As we can see in the second and the third column of Fig. 2, there are diﬀerent start time proﬁle combinations for the ﬂex-oﬀers that participate in the aggregation and result in diﬀerent aggregated ﬂex-oﬀers. Note that the absolute balance of the aggregated ﬂex-oﬀer also depends on the start time proﬁle combinations. For instance, in the second column where we shift the ﬁrst ﬂex-oﬀer for one time unit, we see that the absolute balance of the aggregated ﬂex-oﬀer has reduced. On the other hand, continuing shifting the ﬁrst ﬂex-oﬀer will increase again the 22 E.
As a result, start alignment achieves a low absolute balance and the two greedy techniques do not take advantage of the exploration of the solution space since all the diﬀerences in absolute balance between each possible aggregation are very low. They are very low because even if there might be an earliest start time combination between a positive and a negative ﬂex-oﬀer that reduces the total absolute balance of the mixed ﬂex-oﬀer, the percentage will be too low because the absolute balance is mostly reﬂected by the long proﬁles of the negative ﬂex-oﬀer.
Data Analytics for Renewable Energy Integration: Second ECML PKDD Workshop, DARE 2014, Nancy, France, September 19, 2014, Revised Selected Papers by Wei Lee Woon, Zeyar Aung, Stuart Madnick